ML and physics share a belief in the power of their universal abstractions - all is dynamics in spaces at scales, all is models and data.

The belief is justified because the abstractions work for a big array of problems, to a number of decimal places. Get good enough at solving problems with those universal abstractions, everything starts to look like a solvable problem and it gets easy to lose epistemic humility.

You can combine physics and ML to make large reusable orbital rockets that land themselves. Why shouldn’t be able to solve any of the sometimes much tamer-looking problems they fail to? Even today there was an IEEE article about high failure rates in IT projects…